Protein structural dynamics at the gas/water interface examined by hydrogen exchange mass spectrometry
Bibliographic record
Abstract
Gas/water interfaces (such as air bubbles or foam) are detrimental to the stability of proteins, often causing aggregation. This represents a potential problem for industrial processes, for example, the production and handling of protein drugs. Proteins possess surfactant-like properties, resulting in a high affinity for gas/water interfaces. The tendency of previously buried nonpolar residues to maximize contact with the gas phase can cause significant structural distortion. Most earlier studies in this area employed spectroscopic tools that could only provide limited information. Here we use hydrogen/deuterium exchange (HDX) mass spectrometry (MS) for probing the conformational dynamics of the model protein myoglobin (Mb) in the presence of N(2) bubbles. HDX/MS relies on the principle that unfolded and/or highly dynamic regions undergo faster deuteration than tightly folded segments. In bubble-free solution Mb displays EX2 behavior, reflecting the occurrence of short-lived excursions to partially unfolded conformers. A dramatically different behavior is seen in the presence of N(2) bubbles; EX2 dynamics still take place, but in addition the protein shows EX1 behavior. The latter results from interconversion of the native state with conformers that are globally unfolded and long-lived. These unfolded species likely correspond to Mb that is adsorbed to the surface of gas bubbles. N(2) sparging also induces aggregation. To explain the observed behavior we propose a simple model, that is, "semi-unfolded" ↔ "native" ↔ "globally unfolded" → "aggregated". This model quantitatively reproduces the experimentally observed kinetics. To the best of our knowledge, the current study marks the first exploration of surface denaturation phenomena by HDX/MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".